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Performance of bidimensional location quotients for constructing input–output tables

Author

Listed:
  • Xesús Pereira-López

    (University of Santiago de Compostela
    University of Santiago de Compostela)

  • Napoleón Guillermo Sánchez-Chóez

    (University of Santiago de Compostela
    Escuela Politécnica Nacional)

  • Melchor Fernández-Fernández

    (University of Santiago de Compostela
    University of Santiago de Compostela)

Abstract

This article seeks to verify the extent to which the formulation of two-dimensional location quotients (2D-LQ) entails a methodological advance in building or generating economic accounts related to sub-territories drawing from basic information. The input–output tables of the Euro Area 19 for 2010 and 2015 are references for analysis. We have used five statistics to measure similarity between true domestic coefficient matrices for ten countries (Austria, Belgium, Estonia, France, Germany, Italy, Latvia, Slovakia, Slovenia, and Spain) and the matrices they generate using nonsurvey techniques (CILQ, FLQ, AFLQ, and 2D-LQ). The focus substantially centers on ranking methodological efficiency by comparing the results of the four techniques mentioned above. The scope of the work employs standard parameters (associated with 2D-LQ) as guidance to ascertain the optimum parameters.

Suggested Citation

  • Xesús Pereira-López & Napoleón Guillermo Sánchez-Chóez & Melchor Fernández-Fernández, 2021. "Performance of bidimensional location quotients for constructing input–output tables," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-16, December.
    • Handle: RePEc:spr:jecstr:v:10:y:2021:i:1:d:10.1186_s40008-021-00237-5
    DOI: 10.1186/s40008-021-00237-5
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    References listed on IDEAS

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    1. Anthony T. Flegg & Timo Tohmo, 2016. "Estimating Regional Input Coefficients and Multipliers: The Use of FLQ is Not a Gamble," Regional Studies, Taylor & Francis Journals, vol. 50(2), pages 310-325, February.
    2. Randall Jackson & Alan Murray, 2004. "Alternative Input-Output Matrix Updating Formulations," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 135-148.
    3. Julia Kowalewksi, 2015. "Regionalization of National Input-Output Tables: Empirical Evidence on the Use of the FLQ Formula," Regional Studies, Taylor & Francis Journals, vol. 49(2), pages 240-250, February.
    4. Andrea BONFIGLIO, 2005. "Ca Non-survey Methods Substitute for Survey-based Models ? A Performance Analysis of Indirect Techniques of Estimating I-O Coefficients and Multipliers," Working Papers 230, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    5. A. T. Flegg & C. D. Webber, 1997. "On the Appropriate Use of Location Quotients in Generating Regional Input-Output Tables: Reply," Regional Studies, Taylor & Francis Journals, vol. 31(8), pages 795-805.
    6. Anthony T. Flegg & Leonardo J. Mastronardi & Carlos A. Romero, 2016. "Evaluating the FLQ and AFLQ formulae for estimating regional input coefficients: empirical evidence for the province of Córdoba, Argentina," Economic Systems Research, Taylor & Francis Journals, vol. 28(1), pages 21-37, March.
    7. A. T. Flegg & C. D. Webber, 2000. "Regional Size, Regional Specialization and the FLQ Formula," Regional Studies, Taylor & Francis Journals, vol. 34(6), pages 563-569.
    8. Giuseppe R. Lamonica & Maria C. Recchioni & Francesco M. Chelli & Luca Salvati, 2020. "The efficiency of the cross-entropy method when estimating the technical coefficients of input–output tables," Spatial Economic Analysis, Taylor & Francis Journals, vol. 15(1), pages 62-91, January.
    9. Jan Oosterhaven & Ed C van der Knijff & Gerard J Eding, 2003. "Estimating Interregional Economic Impacts: An Evaluation of Nonsurvey, Semisurvey, and Full-Survey Methods," Environment and Planning A, , vol. 35(1), pages 5-18, January.
    10. Andrea Bonfiglio & Francesco Chelli, 2008. "Assessing the Behaviour of Non-Survey Methods for Constructing Regional Input-Output Tables through a Monte Carlo Simulation," Economic Systems Research, Taylor & Francis Journals, vol. 20(3), pages 243-258.
    11. Roberto Mínguez & Jan Oosterhaven & Fernando Escobedo, 2009. "Cell‐Corrected Ras Method (Cras) For Updating Or Regionalizing An Input–Output Matrix," Journal of Regional Science, Wiley Blackwell, vol. 49(2), pages 329-348, May.
    12. Anthony T. Flegg & Timo Tohmo, 2019. "The regionalization of national input‐output tables: A study of South Korean regions," Papers in Regional Science, Wiley Blackwell, vol. 98(2), pages 601-620, April.
    13. Malte Jahn & Anthony T. Flegg & Timo Tohmo, 2020. "Testing and implementing a new approach to estimating interregional output multipliers using input–output data for South Korean regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 15(2), pages 165-185, April.
    14. Anthony T. Flegg & Timo Tohmo, 2013. "Regional Input--Output Tables and the FLQ Formula: A Case Study of Finland," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 703-721, May.
    15. William A. Schaffer & Kong Chu, 1969. "Nonsurvey Techniques For Constructing Regional Interindustry Models," Papers in Regional Science, Wiley Blackwell, vol. 23(1), pages 83-104, January.
    16. Andrea Bonfiglio, 2009. "On The Parameterization Of Techniques For Representing Regional Economic Structures," Economic Systems Research, Taylor & Francis Journals, vol. 21(2), pages 115-127.
    17. Kirsten S. Wiebe & Manfred Lenzen, 2016. "To RAS or not to RAS? What is the difference in outcomes in multi-regional input--output models?," Economic Systems Research, Taylor & Francis Journals, vol. 28(3), pages 383-402, September.
    18. Michael L. Lahr & Benjamin H. Stevens, 2002. "A Study of the Role of Regionalization in the Generation of Aggregation Error in Regional Input –Output Models," Journal of Regional Science, Wiley Blackwell, vol. 42(3), pages 477-507, August.
    19. Xesús Pereira-López & André Carrascal-Incera & Melchor Fernández-Fernández, 2020. "A bidimensional reformulation of location quotients for generating input–output tables," Spatial Economic Analysis, Taylor & Francis Journals, vol. 15(4), pages 476-493, October.
    20. Ali Reza Jalili, 2000. "Comparison of Two Methods of Identifying Input-Output Coefficients for Exogenous Estimation," Economic Systems Research, Taylor & Francis Journals, vol. 12(1), pages 113-129.
    21. Georgios Lampiris & Christos Karelakis & Efstratios Loizou, 2020. "Comparison of non-survey techniques for constructing regional input–output tables," Annals of Operations Research, Springer, vol. 294(1), pages 225-266, November.
    22. Xiaoyun Zhao & Sung-Goan Choi, 2015. "On the regionalization of input–output tables with an industry-specific location quotient," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(3), pages 901-926, May.
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    Cited by:

    1. Anthony T. Flegg & Guiseppe R. Lamonica & Francesco M. Chelli & Maria C. Recchioni & Timo Tohmo, 2021. "A new approach to modelling the input–output structure of regional economies using non-survey methods," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-31, December.

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    More about this item

    Keywords

    Location quotients; FLQ; 2D-LQ; Non-survey method; Regional input–output tables;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • R19 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Other

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